Explanipedia

Unifying Physics- and Data-Driven Modeling Via Novel Causal Spatiotemporal Graph Neural Network for Interpretable Epidemic Forecasting Open

Shuai Han, Lukas Stelz, Thomas R. Sokolowski, Kai Zhou, H. Stöcker · 2025

Quantum-inspired simulated bifurcation for community detection Open

Wei Li, Yi-Lun Du, Nan Su, Konrad Tywoniuk, Kyle Godbey , et al. · 2025

Community detection by simulated bifurcation Open

Wei Li, Yi-Lun Du, Nan Su, Konrad Tywoniuk, Kyle Godbey , et al. · 2024

Community detection, also known as graph partitioning, is a well-known NP-hard combinatorial optimization problem with applications in diverse fields such as complex network theory, transportation, and smart power grids. The problem's solu…

Pauli-type coupling of spinors and curved spacetime Open

Jürgen Struckmeier, David Vasak, A. Redelbach, H. Stöcker · 2024

In this study we prove that the Pauli interaction—which is associated with a length parameter—emerges when the minimal coupling recipe is applied to the non-degenerate version of the Dirac Lagrangian. The conventional Dirac Lagrangian is r…

Canonical Ensemble vs. Grand Canonical Ensemble in the Description of Multicomponent Bosonic Systems Open

D. Anchishkin, V. Gnatovskyy, D. Zhuravel, V. Karpenko, I. N. Mishustin , et al. · 2024

The thermodynamics of a system of interacting bosonic particles and antiparticles in the presence of the Bose–Einstein condensate is studied in the framework of a Skyrme-like mean-field model. It is assumed that the total charge density (i…

Mass and tidal parameter extraction from gravitational waves of binary neutron stars mergers using deep learning Open

Shriya Soma, H. Stöcker, Kai Zhou · 2024

Gravitational Waves (GWs) from coalescing binaries carry crucial information about their component sources, like mass, spin and tidal effects. This implies that the analysis of GW signals from binary neutron star mergers can offer unique o…

Crater formation and deuterium production in laser irradiation of polymers with implanted nano-antennas Open

L. P. Csernai, I. N. Mishustin, L. M. Satarov, H. Stöcker, L. Bravina , et al. · 2023

Recent validation experiments on laser irradiation of polymer foils with and without implanted golden nanoparticles are discussed. First we analyze characteristics of craters, formed in the target after its interaction with the laser beam.…

Mass and tidal parameter extraction from gravitational waves of binary neutron stars mergers using deep learning Open

Shriya Soma, H. Stöcker, Kai Zhou · 2023

Gravitational Waves (GWs) from coalescing binaries carry crucial information about their component sources, like mass, spin and tidal effects. This implies that the analysis of GW signals from binary neutron star mergers can offer unique o…

Examination of nucleon distribution with Bayesian imaging for isobar collisions Open

Y. Cheng, Shuzhe Shi, Y. G., H. Stöcker, Kai Zhou · 2023

Relativistic collision of isobaric systems is found to be valuable in differentiating the nucleon distributions for nuclei with the same mass number. In recent contrast experiment of $^{96}_{44}$Ru + $^{96}_{44}$Ru versus $^{96}_{40}$Zr + …

PIC simulations of laser-induced proton acceleration by resonant nanoantennas for fusion Open

I. Papp, L. Bravina, Mária Csete, Archana Kumari, I. N. Mishustin , et al. · 2023

Rapid recent development in laser technology and methods learned from relativistic heavy ion physics led to new possibilities for fusion. Using a Hydrogen rich UDMA-TEGDMA polymer fusion target, laser irradiation ionizes the target. If we …

A neural network reconstruction of the neutron star equation of state via automatic differentiation Open

Shriya Soma, Lingxiao Wang, Shuzhe Shi, H. Stöcker, Kai Zhou · 2023

In this work, we reconstruct the cold and dense matter equation of state~(EoS) from the current observational neutron star data. We achieve this by using a physics-based deep learning method that utilizes the Automatic Differentiation tech…

Reconstructing the neutron star equation of state from observational data via automatic differentiation Open

Shriya Soma, Lingxiao Wang, Shuzhe Shi, H. Stöcker, Kai Zhou · 2023

Neutron star observables like masses, radii, and tidal deformability are direct probes to the dense matter equation of state (EoS). Here, a novel deep learning method that optimizes an EoS in the automatic differentiation framework of solv…

Identifying lightning structures via machine learning Open

Lingxiao Wang, B. M. Hare, Kai Zhou, H. Stöcker, O. Schölten · 2023

Humankind, Energy and the Climate - A EURO-CORDEX Analysis Open

Markus Schlott, Omar El Sayed, Mariia Bilousova, Chen Li, Filippo Guidi , et al. · 2023

Climate change is going to alter the appearance of planet Earth throughout the century and beyond unprecedentedly. Therefore the United Nations (UN) decided to classify climate action as the 13th Sustainable Development Goal (SDG); right a…

A hybrid approach for declustering of earthquake catalogs Open

Jonas Köhler, Wei Li, Johannes Faber, Georg Rümpker, H. Stöcker , et al. · 2023

Usually, the earthquake catalog for a given region represents a collection of all detected and localized earthquakes and, thus, contains not only the main shocks, but also fore- and aftershocks. In order to perform an independent seismic e…

Kinetic model of resonant nanoantennas in polymer for laser induced fusion Open

I. Papp, L. Bravina, Mária Csete, A. Leela Siva Kumari, I. N. Mishustin , et al. · 2023

Studies of resilience of light-resonant nanoantennas in vacuum are extended to consider the case of polymer embedding. This modifies the nanoantenna’s lifetime and resonant laser pulse energy absorption. The effective resonance wavelength …

The equilibrium and dynamical cumulants of QCD chiral order parameter with parametric Landau free energy Open

Lijia Jiang, H. Stöcker, Jun-Hui Zheng · 2023

Examination of nucleon distribution with Bayesian imaging for isobar collisions Open

Yi‐Lin Cheng, Shuzhe Shi, Y. G., H. Stöcker, Kai Zhou · 2023

Relativistic collision of isobaric systems is found to be valuable in differentiating the nucleon distributions for nuclei with the same mass number. In recent contrast experiment of $^{96}_{44}\text{Ru}+^{96}_{44}\text{Ru}$ versus $^{96}_…

Identifying Lightning Structures Via Machine Learning Open

Lingxiao Wang, B. M. Hare, Kai Zhou, H. Stöcker, O. Schölten · 2023

A physics-based neural network reconstruction of the dense matter equation of state from neutron star observables Open

Shriya Soma, Lingxiao Wang, Shuzhe Shi, H. Stöcker, Kai Zhou · 2023

We introduce a novel technique that utilizes a physics-driven deep learning method to reconstruct the dense matter equation of state from neutron star observables, particularly the masses and radii. The proposed framework involves two neur…

On the cosmological constant in the deformed Einstein–Cartan gauge gravity in De Donder–Weyl Hamiltonian formulation Open

David Vasak, Johannes Kirsch, Jürgen Struckmeier, H. Stöcker · 2022

A modification of the Einstein–Hilbert theory, the Covariant Canonical Gauge Gravity (CCGG), leads to a cosmological constant that represents the energy of the space–time continuum when deformed from its (A)dS ground state to a flat geomet…

Kinetic Model Evaluation of Dynamical Properties of Nanaorod Antennas Embedded in a Polymer Carrying the Nuclei of Fusion Fuel Open

I. Papp, L. Bravina, Mária Csete, Archana Kumari, I. N. Mishustin , et al. · 2022

Recently laser induced fusion with simultaneous volume ignition, a spin-off from relativistic heavy ion collisions, was proposed, where implanted nanoantennas regulated and amplified the light absorption in the fusion target. Studies of re…

EPick: Attention-based multi-scale UNet for earthquake detection and seismic phase picking Open

Wei Li, Megha Chakraborty, Darius Fenner, Johannes Faber, Kai Zhou , et al. · 2022

Earthquake detection and seismic phase picking play a crucial role in the travel-time estimation of P and S waves, which is an important step in locating the hypocenter of an event. The phase-arrival time is usually picked manually. Howeve…

Predicting Influenza A Virus Infection in the Lung from Hematological Data with Machine Learning Open

Suneet Singh Jhutty, Julia D. Boehme, Andreas Jeron, Julia Volckmar, Kristin Schultz , et al. · 2022

During the course of respiratory infections such as influenza, we do have a very limited view of immunological indicators to objectively and quantitatively evaluate the outcome of a host. Methods for monitoring immunological markers in a h…

A study on small magnitude seismic phase identification using 1D deep residual neural network Open

Wei Li, Megha Chakraborty, Yu Sha, Kai Zhou, Johannes Faber , et al. · 2022

Reliable seismic phase identification is often challenging especially in the circumstances of low-magnitude events or poor signal-to-noise ratio. With improved seismometers and better global coverage, a sharp increase in the volume of reco…

Reconstructing the neutron star equation of state from observational data via automatic differentiation Open

Shriya Soma, Lingxiao Wang, Shuzhe Shi, H. Stöcker, Kai Zhou · 2022

Neutron star observables like masses, radii, and tidal deformability are direct probes to the dense matter equation of state~(EoS). A novel deep learning method that optimizes an EoS in the automatic differentiation framework of solving in…

Neural network reconstruction of the dense matter equation of state from neutron star observables Open

Shriya Soma, Lingxiao Wang, Shuzhe Shi, H. Stöcker, Kai Zhou · 2022

The Equation of State (EoS) of strongly interacting cold and hot ultra-dense QCD matter remains a major challenge in the field of nuclear astrophysics. With the advancements in measurements of neutron star masses, radii, and tidal deformab…

Kinetic Model Evaluation of the Resilience of Plasmonic Nanoantennas for Laser-Induced Fusion Open

I. Papp, L. Bravina, Mária Csete, A. Leela Siva Kumari, I. N. Mishustin , et al. · 2022

Recently, a new version of laser-induced fusion was proposed where implanted nanoantennas regulated and amplified the light absorption in the fusion target [L.P. Csernai et al., Phys. Wave Phenom. 28, 187–99 (2020)]. In this paper we estim…

Shared Data and Algorithms for Deep Learning in Fundamental Physics Open

L. Benato, Erik Buhmann, M. Erdmann, P. Fackeldey, Jonas Glombitza , et al. · 2022

We introduce a Python package that provides simple and unified access to a collection of datasets from fundamental physics research—including particle physics, astroparticle physics, and hadron- and nuclear physics—for supervised machine l…

CREIME -- A Convolutional Recurrent model for Earthquake Identification and Magnitude Estimation Open

Megha Chakraborty, Darius Fenner, Wei Li, Johannes Faber, Kai Zhou , et al. · 2022

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Journal of Geophysical Research - Solid Earth. ESSOAr is a venue for early communication or feedback before peer review. Data may be pre…

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